It is a well-known fact that neural networks can approximate the output of any continuous mathematical function, no matter how complicated it might be. Take for instance the function below: Though it ...

👩‍💻This repository provides Python implementations of a variety of fundamental algorithms and problem-solving techniques. From Knapsack and TSP to BFS, DFS, and more, explore practical examples to ...

Here are a some implementations of various approximation algorithms for the optimal Travelling Salesperson Tour in 2D Euclidean Space. Additionally there are some helper algorithms such as Kruskal's ...

I built a scalable N-Body gravitational simulator in Python using a Quadtree, replacing O(N²) interactions with an O(N log N) hierarchical approximation. I started from a simple question: how do you ...

Dive into Python Physics Lesson 23 and discover what happens when approximations fail in dipole electric fields. In this lesson, we explore the limitations of common approximation methods in physics ...